Multifactorial optimization of endothelial cell growth using modular synthetic extracellular matrices.

TitleMultifactorial optimization of endothelial cell growth using modular synthetic extracellular matrices.
Publication TypeJournal Article
Year of Publication2011
AuthorsJP Jung, JV Moyano, and JH Collier
JournalIntegrative Biology : Quantitative Biosciences From Nano to Macro
Start Page185
Pagination185 - 196
Date Published03/2011

Extracellular matrices (ECMs) are complex materials, containing at least dozens of different macromolecules that are assembled together, thus complicating their optimization towards applications in 3D cell culture or tissue engineering. The natural complexity of ECMs has limited cell-matrix investigations predominantly to experiments where only one matrix component is adjusted at a time, making it difficult to uncover interactions between different matrix components or to efficiently determine optimal matrix compositions for specific desired biological responses. Here we have developed modular synthetic ECMs based on peptide self-assembly whose incorporation of multiple different peptide ligands can be adjusted. The peptides can co-assemble in a wide range of combinations to form hydrogels of uniform morphology and consistent mechanical properties, but with precisely varied mixtures of peptide ligands. The modularity of this system in turn enabled multi-factorial experimental designs for investigating interactions between these ligands and for determining a multi-peptide matrix formulation that maximized endothelial cell growth. In cultures of HUVECs, we observed a previously unknown antagonistic interaction between the laminin-derived peptide YIGSR and RGDS-mediated cell attachment and growth. We also identified an optimized combination of self-assembled peptides bearing the ligands RGDS and IKVAV that led to endothelial cell growth equivalent to that on native full-length fibronectin. Both of these findings would have been challenging to uncover using more traditional one-factor-at-a-time analyses.

Short TitleIntegrative Biology : Quantitative Biosciences From Nano to Macro